Automatic Segmentation of Hindi Speech into Syllable-Like Units

To develop the high-quality Text-to-Speech (TTS) system, appropriate segmentation of continuous speech into the syllabic units placed an important role. The research work has been implemented for automatic syllable based speech segmentation technique for continuous speech for the Hindi language. The experiments were conducted by using the energy convex hull approach for clean, continuous speech for Hindi. In this method, the Savitzky-Golay filter was applied on the short term energy (STE) signal to increase the signal to noise ratio (SNR), followed by applying the median filter to preserve the boundaries, hence smoothing the energy curve. Also, the Hamming sliding-window was applied twice on speech signal to get the more accurate depth of convex hull valleys. Further, the algorithm was tested on 50 unique utterances chosen from the travel domain. The accuracy of the proposed algorithm has been calculated and obtains that 76.07% syllables have time-error less than 30 ms with manual segmentation reference. The performance of the proposed algorithm is also analyzed and gives better-segmented accuracy as compared to the existing group delay segmentation technique for fricatives or nasal sounds. The syllable base segmented database is suitable for the speech technology system for Hindi in the travel domain.